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This thesis examines the differences and similarities in the paradigmatic development of the central paradigms Traditional, Neural Networks, and the Evolutionary paradigm within Artificial Intelligence in the time period from the 50’s to modern age. In order to examine the differences and similarities, a comparative analysis method was applied to highlight how the concept of Artificial Intelligence has been approached within the different research paradigms of traditional, neural networks and the evolutionary paradigm. Indeed, a comparative analysis methodology allows for a deep analysis of both differences and similarities but also calls for an extended perspective of related philosophical, cultural, social and information processing influences. It is fundamental to understand these influencers in order to outline a comprehensive answer to how the different paradigms utilizes different approaches to examine Artificial Intelligence. The analysis has been conducted involving a hermeneutics approach which has resulted in the suggestion that the different paradigms has connections to philosophical theories such as rationalism and empiricism.